Jiawei Li

Brief Introduction

Jiawei Li (李佳玮 , , ❤), I'm a PhD student of Computer Science in College of Intelligence and Computing in Tianjin University. My skills include Deep Learning, Machine Learning and Data Visualization (Python, R). My doctoral research direction is AI IN HEALTH CARE. Although I am working on AI IN HEALTH CARE now, I am not limited to that. Looking forward to the arrival of AGI in the near future.

Resume: CHINESE / ENGLISH

Experience

• 2023.09-2024.09: CSC Joint PhD, The Centre for Data Science and Machine Learning, National University of Singapore, Singapore
• 2022.05-2023.05: Researcher (Internship), Artificial Intelligence Laboratory, Tencent Technology Co. Ltd., Shenzhen, China
• 2022.01-2025.01: Researcher (Internship), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
• 2021.09-2025.01: PhD, College of Intelligence and Computing, Tianjin University, Tianjin, China
• 2021.02-2021.08: R & D Engineer, Huawei Technologies Co. Ltd., Beijing, China
• 2020.07-2020.09: R & D Engineer, Sangfor Technologies Inc., Shenzhen, China
• 2018.09-2021.01: Master, College of Intelligence and Computing, Tianjin University, Tianjin, China
• 2014.09-2018.06: Bachelor, School of Computer Science and Engineering, Tianjin University of Technology, Tianjin, China

Project

• 2024.01.01-2026.12.31: Guangdong Basic and Applied Basic Research Foundation, 2024A1515011960. (Participation)

Publication

[Google Scholar] [Research Gate] [Details]
( #: indicating equal contribution; *: indicating corresponding author. )

2024

1. Shi Tang#, Yu Han#, Limin Jiang, Jingjing Zhang, Jiawei Li, Ibrahim Zamit, Yanlin Wang*. Neuroimaging-transcriptomic associations in aging and Parkinson's disease progression. Annals of Neurology. (Submitted) (SCI:1;IF:11.2)
2. Zhiliang Xia, Shiqiang Ma, Jiawei Li, Yan Guo, Limin Jiang, Jijun Tang*. RecGOBD: Accurate Recognition of Gene Ontology Related Brain Development Protein Functions through Multi-Feature Fusion and Attention Mechanisms. ACM Computing Surveys. (Submitted) (SCI:1;IF:16.60)

2023

1. Jiawei Li, Shizhan Chen, Shiqiang Ma*, Fei Guo*, Jijun Tang*. MixUNet: Mix the 2D and 3D Models for Robust Medical Image Segmentation. BIBM 2023: IEEE International Conference on Bioinformatics & Biomedicine. (CCF:B)
2. Mengyuan Zhao, Jiawei Li, Ma Ke, Jijun Tang*, Fei Guo*. scHGR: An automated annotation tool for single-cell transcriptome data combining transcriptomic profile with genomic relation. Nucleic Acids Research. (SCI:1;IF:14.90)
3. Ke Ma, Jiawei Li, Mengyuan Zhao, Jijun Tang*, Fei Guo*. PPRTGI: A Personalized PageRank Graph Neural Network for TF-target Gene Interaction Detection. IEEE-ACM Transactions on Computational Biology and Bioinformatics. (CCF:B)
4. Fang Wang, Chunpu Liu, Jiawei Li, Fan Yang, Jiangning Song, Jianhua Yao*, Guohua Wang*. SPDB: comprehensive resource and knowledgebase for proteomic data at the single-cell resolution. Nucleic Acids Research. (SCI:1;IF:14.90)
5. Jingfeng Ou, Jiawei Li, Zhiliang Xia, Shurui Dai, Limin Jiang, Yan Guo*, Jijun Tang*. RFAE: A high-robust feature selector based on fractal autoencoder. EXPERT SYSTEMS WITH APPLICATIONS. (SCI:1;IF:8.50)
6. Yanlin Wang, Shiqiang Ma, Ruimin Ma, Linxia Xiao, Jiawei Li, Shi Tang, Yanjie Wei*, Yi Pan*. Distinct Neurodevelopmental Patterns and Intermediate Fusion-Based Predictive Modeling in Autism. Brain (SCI:1;IF:14.5)

2022

1. Jiawei Li, Fan Yang, Fang Wang, Shizhan Chen, Yu Rong, Peilin Zhao, Jianhua Yao*, Jijun Tang*, Fei Guo*. Integrating Prior Knowledge with Graph Encoder for Gene Regulatory Inference from Single-Cell RNA-Seq Data. BIBM 2022: IEEE International Conference on Bioinformatics & Biomedicine. (CCF:B)

2021

1. Limin Jiang, Hui Yu, Jiawei Li, Jijun Tang, Yan Guo*, Fei Guo*. Predicting MHC class I binder: existing approaches and a novel recurrent neural network solution. Briefings in Bioinformatics. (SCI:1;IF:13.994) [Link]
2. Yuqian Pu, Jiawei Li, Jijun Tang*, Fei Guo*. DeepFusionDTA: drug-target binding affinity prediction with information fusion and hybrid deep-learning ensemble model. IEEE-ACM Transactions on Computational Biology and Bioinformatics. (CCF:B)
3. Jiaqi Ding, Jie Song, Jiawei Li, Jijun Tang, Fei Guo*. Two-Stage Deep Neural Network via Ensemble Learning for Melanoma Classification. Frontiers in Bioengineering and Biotechnology. (SCI:2;IF:5.43)

2020

1. Jiawei Li, Yuqian Pu, Jijun Tang*, Quan Zou*, Fei Guo*. DeepATT: a hybrid category attention neural network for identifying functional effects of DNA sequences. Briefings in Bioinformatics. (SCI:1;IF:13.994) [Link] [Code] [Pdf]
2. Jiawei Li, Yuqian Pu, Jijun Tang*, Quan Zou*, Fei Guo*. DeepAVP: a dual-channel deep neural network for identifying variable-length antiviral peptides. IEEE Journal of Biomedical and Health Informatics. (SCI:1;IF:7.021) [Link] [Server] [Pdf]
3. Jie Song^#, Jiawei Li^#, Shiqiang Ma, Jijun Tang*, Fei Guo*. Melanoma Classification in Dermoscopy Images via Ensemble Learning on Deep Neural Network. BIBM 2020: IEEE International Conference on Bioinformatics & Biomedicine. (CCF:B)
4. Yinuo Lv, Zhen Zhang, Jiawei Li, Wenying He, Yijie Ding*, Fei Guo*. iEnhancer-KL: a novel predictor for identifying enhancer by position specific of nucleotide composition. IEEE-ACM Transactions on Computational Biology and Bioinformatics. (CCF:B)

Open Source Project

Contact info

• Email: ljwstruggle@gmail.com (main)
• Email: ljwstruggle@qq.com